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Bachelor's Degree AND 5+ years experience in product management OR equivalent experience. 3+ years of experience leading ambiguous product areas, defining requirements, developing roadmaps, and working with multi-disciplinary teams to execute them. 2+ years of experience building ML-powered or LLM-powered products. Hands-on experience with LLM APIs (e.g. OpenAI, Anthropic, Azure OpenAI), embeddings, vector databases, and tool use. Hands-on experience with prompt design, context window management, and model evaluation. 2+ years of hands-on experience in building retrieval and/or recommendation systems, driving measurable improvements in relevance, engagement, and conversion through data-driven experimentation. Skilled in translating user intent into product strategy and collaborating closely with engineering and ML teams to deliver scalable, personalized experiences. 1+ years of experience in building LLM applications with familiarity in agent and orchestration frameworks, tool use, LLM evaluations and driving efficiency improvements. Technical depth in software development, data science and machine learning. While you are not expected to write code on the critical path, you're able to define and execute on zero-to-one prototypes, reason over large amounts of data, and speak the language of the engineers and researchers you work with. Experience using and applying Large Language Models. 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Accountable to own the status of key projects, proactively identifying risks and proposing solutions to ensure timely delivery. Bachelor's Degree in Computer Science, Philosophy, Linguistics, Psychology, Literature, or related discipline AND 1+ years experience in context engineering with foundational software engineering knowledge. 3+ years experience working in a fast-paced environment, managing multiple priorities, and adapting to changing requirements and deadlines. Hands-on experience with prompt design, context window management, and model evaluation. 2+ years of experience shipping consumer-facing products. You've brought products to market, collected user feedback, defined success metrics and iteratively improved products. 1+ years of experience in building LLM applications with familiarity in agent and orchestration frameworks, tool use, LLM evaluations and driving efficiency improvements. Technical depth in software development, data science and machine learning. 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Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience. 2+ years direct, hands-on collaboration with model researchers and ML engineers in areas such as training runs, data evaluation, infrastructure, coding, or safety. Experience building and shipping data pipelines or evaluation systems personally. A technical postgraduate degree is strongly preferred; a PhD is ideal but not mandatory. Demonstrated ability to bring enterprise or developer products to market by deeply engaging with end customers. Identify and prioritize language / coding / multimodal issues and work with researchers to find a path to resolution. Create novel data collection tasks for taskers to evaluate models and to collect training data for fine-tuning. Create model prototypes to prove out new feature directions and scope projects. Collaborate closely with teams on infrastructure, data engineering, pre-training, post-training, and product feedback Foster a culture of collaboration, continuous improvement, and growth. 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Experience with AI features and data-informed iteration.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://microsoftai.eightfold.ai/careers/job/1970324837141017", "isPrivate": false}, {"id": 1970324837141016, "name": "Senior Product Manager \u2013 Mobile Experiences (iOS/Android)", "location": "Mountain View, California, United States", "locations": ["Mountain View, California, United States"], "hot": 0, "department": "Copilot (P0PS)", "business_unit": "Microsoft AI (QIA5)", "t_update": 1765679686, "t_create": 1761848394, "ats_job_id": 1970324837141016, "display_job_id": 1970324837141016, "type": "ATS", "id_locale": "1970324837141016-en", "job_description": "A motivated, detail-oriented Product Manager who: Has experience shipping consumer mobile features and thrives in execution-focused roles. Collaborates deeply with Design on interaction and visual details. 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In this role, you\u2019ll partner closely with senior product leaders, designers, and engineers to deliver native iOS and Android features with pixel-level polish and measurable impact. You\u2019ll play a critical role in integrating Copilot into mobile experiences and ensuring execution excellence. This is an opportunity to contribute to best-in-class mobile AI experiences for millions of users while learning from and supporting a lead PM driving strategy. What we're looking for A motivated, detail-oriented Product Manager who: Has experience shipping consumer mobile features and thrives in execution-focused roles. Collaborates deeply with Design on interaction and visual details. Understands mobile engineering fundamentals (Swift, SwiftUI, Jetpack, Kotlin). Uses experimentation and telemetry to guide decisions. Brings strong customer empathy and clarity in execution. Microsoft\u2019s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction. Responsibilities Support the lead PM in defining and refining vision, roadmap, and KPIs for iOS/Android experiences. Write PRDs/specs and drive execution from experiment to GA with high quality. Champion mobile-native quality: startup time, perceived performance, offline/online ergonomics. Implement A/B experimentation and telemetry practices with accessibility guardrails. 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